Natural Language Processing with Python#
This section includes notes on natural language processing with Python. More specifically, it is about extracting meaningful structures and patterns from massive collections of texts.
Topics may include:
Text Normalization Techniques
Important Python libraries for NLP
Traditional (Shallow) Machine Learning
Text Classification
Text Summarization
Topic Modeling
Text Similarity and Clustering
Semantic Analysis and Network
Sentiment Analysis
Word Embeddings and Deep Learning
Recurrent Neural Network and LSTM
Sequence-to-Sequence and Machine Translation
Transfer Learning Using BERT
Hyper-Parameter Tuning (Grid Search and Cross Validation)
Explainable AI (LIME)